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Abstract:

A healthcare management apparatus for determining a health condition of
subjects is provided.
The following configuration realizes the above object.
The healthcare management apparatus includes an acquiring means for
acquiring physical data and blood components data of subjects, data
conversion formula and data determination criteria; and a processing
means for converting the physical data and the blood components data into
relative values by using the data conversion formula, and for determining
health condition of the subjects by using the data determination
criteria.
Preferably, the acquiring means further comprise health assessment formula
and health condition determination criteria. The processing means
calculates a health condition determination relative values by combining
two or more of the relative values and/or the health condition
determination relative values and using total health assessment formula
and determines a total health condition of subjects by checking the total
health condition determination relative values with total health
condition determination criteria. The acquiring means also includes a
memory and a communication means.

Claims:

1. A healthcare management apparatus comprising:an acquiring means for
acquiring physical data and blood components data of subjects, data
conversion formula and data determination criteria; anda processing means
for converting the physical data and the blood components data into
relative values by using the data conversion formula, and for determining
health condition of the subjects by using the data determination
criteria.

2. The healthcare management apparatus of claim 1, wherein:the acquiring
means further acquires health assessment formula and health condition
determination criteria; andthe processing means combines two or more of
the physical data, the blood components data and the relative values to
calculate health condition determination relative values using the health
assessment formula, and then checks the health condition determination
relative values with the health condition determination criteria to
determine a risk of progression to lifestyle diseases of subjects.

3. The healthcare management apparatus of claim 2, wherein:the acquiring
means further acquires total health assessment formula and total health
condition determination criteria; andthe processing means combines two or
more of the relative values and the health condition determination
relative values to calculate total health condition determination
relative values using the total health assessment formula, and then
checks the total health condition determination relative values with the
total health condition determination criteria to determine a total health
condition of subjects.

4. The healthcare management apparatus of claim 1, wherein:the acquiring
means further acquires identification characters including information on
sex, age and race of subjects.

5. The healthcare management apparatus of claim 4, wherein:the data
conversion formula is a pattern table that shows a relationship between
measurement values and relative values.

6. The healthcare management apparatus of claim 5, wherein:multiple kinds
of the pattern tables are acquired according to sex, age and race; andthe
processing means determines at least one of sex, age and race of
subjects, and decides the pattern table to be used.

7. The healthcare management apparatus of claim 1, further comprising an
input means.

8. The healthcare management apparatus of claim 1, further comprising a
display for displaying determination results.

9. The healthcare management apparatus of claim 8, wherein:the acquiring
means further acquires health improvement method data; andthe processing
means checks determination results with the health improvement method
data, and lets the display show the determination results as well as a
health improvement method corresponding to the determination results.

16. The health condition determination method of claim 14 further
comprising:a total health condition determination relative values
calculating step for calculating relative values used in total health
condition determination by combining two or more of the relative values
and/or the health condition determination relative values and using total
health assessment formula; anda total health condition determination step
for determining a total health condition of subjects by checking the
total health condition determination relative values with total health
condition determination criteria.

17. The health condition determination method of claim 15 further
comprising:a total health condition determination relative values
calculating step for calculating relative values used in total health
condition determination by combining two or more of the relative values
and/or the health condition determination relative values and using total
health assessment formula; anda total health condition determination step
for determining a total health condition of subjects by checking the
total health condition determination relative values with total health
condition determination criteria.

20. The health condition determination method of claim 18, whereinblood
components data used in the specific proteins in blood determination
includes at least one analysis data of adiponectin, leptin, resistin and
TNF-.alpha..

21. The health condition determination method of claim 19, whereinblood
components data used in the specific proteins in blood determination
includes at least one analysis data of adiponectin, leptin, resistin and
TNF-.alpha..

22. The health condition determination method of claim 13, whereina
pattern table showing a relationship between measurement values and
relative values is used as the data conversion formula.

23. The health condition determination method of claim 22 further
comprising,a pattern table deciding step for deciding the pattern table
by determining at least one of sex, age and race of subjects.

24. A display method of health condition determination results
comprising,a display step for displaying determination results of the
health condition determination method of claim 21 together with a graph
showing relative values of the analysis data of adiponectin, leptin,
resistin and TNF-.alpha..

25. The display method of health condition determination results of claim
24,whereinthe graph is arranged so that indices having a strong degree of
the antagonistic relationship and/or correlation are placed adjacently to
each other.

26. The display method of health condition determination results of claim
24, further comprising a step for displaying time course information of
measurement values of the four components together with the graph.

27. The display method of health condition determination results of claim
24, further comprising a step for displaying a warning message when any
determination result of the four components exceeds a criteria value.

28. The display method of health condition determination results of claim
24, further comprising a step for displaying the determination results
and a health improvement method of subjects corresponding to the
determination results.

29. The display method of health condition determination results of claim
24, further comprising a step for displaying X1Y1, X2Y2, X3Y2 and X4Y1,
wherein:X1 is the adiponectin level; X2 is the leptin level; X3 is the
resistin level; X4 is the TNF-.alpha. level; and Y1 and Y2 are
coefficients based on an obesity degree determined from Body Mass Index
relative values.

30. The display method of health condition determination results of claim
29, further comprising a step for displaying X1Y1 at the right edge of
the waist, X2Y2 at the right edge of the chest, X3Y2 at the left edge of
the chest, and X4Y1 at the left edge of the waist in a human-shaped
model.

31. The display method of health condition determination results of claim
29, further comprising a step for displaying X1Y1 at the back edge of the
waist, X2Y2 at the back edge of the abdomen, X3Y2 at the front edge of
the abdomen, and X4Y1 at the front edge of the waist in a human-shaped
model.

Description:

BACKGROUND OF THE INVENTION

[0001]1. Field of the Invention

[0002]The present invention relates to an apparatus and a method for
proposing the healthcare management using physical data and blood
components data and thus determining the health conditions of the
subjects.

[0003]2. Background Art

[0004]In recent years, many people have been suffering from cardiovascular
diseases due to lifestyle diseases such as diabetes and high blood
pressure. Lifestyle diseases, which sometimes occur resulting from
genetic factors, can be generally prevented by improvement of daily life
such as diet and exercise. In this circumstance, National Cholesterol
Education Program (NCEP) has published a simple definition that
determines as metabolic syndrome when any three of five diagnostic items
(waist circumference, blood glucose level, blood pressure, neutral fat
level and HDL cholesterol level) meet its criteria.

[0005]Therefore, it is required to build a system to easily manage the
risk for progression to lifestyle diseases and to allow subjects to
improve lifestyle in the early stage.

[0006]To determine the lifestyle diseases, it is necessary to measure the
amount of the substances (glucose, proteins, lipids, etc.) contained in
biological samples such as blood. In addition, in order to understand the
risks for progression of lifestyle diseases, biological samples such as
saliva, blood and urine may be used in determination of health condition.
However, since the amounts of the substances contained in the biological
samples are greatly differed between individuals, there is a problem of
determining health condition or medical conditions only by the
measurement results of substances.

[0007]Patent documents 1 to 4 suggest a method for determining health
condition of subjects using biological samples. Patent document 5
suggests an analytical microchip sensor that could apply to measurement
of substances in biological samples.

[0008]It is reported in Non-patent documents 1 to 6 that the relationship
between blood components (proteins) and the risk of lifestyle diseases.

[0023]However, this technology provides only the determination of
metabolic syndrome according to standards of Japan Society for the Study
of Obesity (JASSO). Therefore, it is difficult to precisely determine the
progression to lifestyle diseases due to other reasons except metabolic
syndrome.

[0024]Patent document 2 proposes a method to determine the metabolic
syndrome that is closely related to lifestyle disease with measuring the
choline-type plasmalogen and ethanol-amine-type plasmalogen level in
serum.

[0025]However, this technology shows only low correlation between the
measured plasmalogen level in serum and lifestyle diseases (diabetes,
arteriosclerosis, hypertension, hyperlipidemia, etc.), therefore, it is
difficult to exactly determine metabolic syndrome and the risk of
lifestyle diseases.

[0026]Patent document 3 proposes a method to determine the degree of
stress by using a combination of salivary ingredients and indicators
other than salivary components.

[0027]However, in this technology, the diagnosis of stress shows only
"Normal" or "Attention" and the determination range of each area is wide.
Therefore, there is a problem of being difficult for users to understand
the degree of improvement in symptoms.

[0028]Patent document 4 proposes a method to collect data of several
components in blood and then to make a diagnosis using a pattern of such
measurements.

[0029]In this technique, a diagnosis is made using several items of blood
components as indices. However, because this technology only provides a
list of the measurements (absolute values) and determines whether the
values are normal or not, the user do not exactly understand the risk.
Moreover, although several items of blood components are used as indices,
the relation among the items is not identified clearly.

[0030]The relation between blood components and lifestyle diseases
described in Non-patent documents 1 to 6 is as follows.

(Adiponectin)

[0031]It is known that adiponectin level in blood is decreased with
obesity and insulin resistance while the level is increased because of
body weight loss (improvements in obesity). In addition, the previous
research has revealed anti-diabetic and anti-atherogenic effects of
adiponectin (cf. Non-patent documents 1, 3 and 4.).

(Leptin)

[0032]Leptin is produced in fat cells, and conveys the amount of body fat
to the brain to adjust metabolism and appetite, thus having the function
of appetite control (cf. Non-patent document 2.).

(Resistin)

[0033]Resistin is One Kind of Adipokine, which Causes Insulin Resistance.
Resistin causes insulin resistance at fat cells, muscle cells, liver
cells and the like, and thus is said to be the cause of increasing
glucose in blood. In addition, resistin increases the production of
endothelin that is said to be the cause of high blood pressure, thus may
promote arterial sclerosis, and is deeply involved in lifestyle diseases
including metabolic syndrome (cf. Non-patent literature 5.).

(TNF-α)

[0034]The secretion amount of TNF-α is increased when fat cells
enlarge. TNF-α serves to inhibit the activation of insulin
receptors in fat cells and muscle cells, and thus may lead to insulin
resistance and high concentration of glucose in blood. Therefore,
TNF-α may cause a type 2 diabetes (cf. Non-patent document 6.).

SUMMARY OF THE INVENTION

[0035]It is difficult to accurately grasp a health condition only by
measuring substances that serves as indices of the health condition, and
stress-induced diseases and by comparing them with the criteria value of
each substance. Therefore, a health condition management apparatus is
required that can easily determine the health condition of subjects
accurately and the risk of progression to lifestyle diseases.

[0036]Conventional apparatuses for determining metabolic syndrome, which
use the definition of National Cholesterol Education Program (NCEP), the
International Diabetes Federation (IDF), Japan Society for the Study of
Obesity (JASSO) or the like, can easily make the determination of
metabolic syndrome. However, only by the determination of metabolic
syndrome, it is difficult to predict the possibility or risk of
progression to lifestyle diseases in view of health condition of
subjects.

[0037]The present invention is made in cultivating of the problems
associated with the conventional technologies. The object of the present
invention is to provide an apparatus and a method for determining health
condition, which can precisely determine personal health condition and
the risk of progression to lifestyle diseases and thus allows a proposal
of improvement in health to the people. Moreover, the present invention
aims to provide an apparatus and a method for displaying the health
condition results so that the subjects may visually understand their
health condition, which results in early improvement in health.

[0038]The present invention relating to a health condition determination
apparatus to solve the above problems is characterized by comprising:

[0040]a processing means for converting the physical data and the blood
components data into relative values by using the data conversion
formula, and for determining health condition of the subjects by using
the criteria for determining data.

[0041]With this apparatus, the health condition of the subjects and the
risk of progression to lifestyle diseases can be easily and accurately
determined. In addition, the improvement in lifestyle can be proposed to
the subjects according to the results of the health condition
determination, and thus the progression to lifestyle diseases can be
prevented in advance.

[0043]In the above configuration, the acquiring means may further comprise
health assessment formula and health condition determination criteria,
and the processing means combines two or more of the physical data, the
blood components data and the above relative values to calculate health
condition determination relative values using the health assessment
formula, and check the health condition determination relative values
with the health condition determination criteria to determine the risk of
progression to lifestyle diseases based on health condition of subjects.

[0044]It is preferable to combine several physical data and blood
components data in determination for the risk of progression to lifestyle
diseases such as metabolic syndromes, hyperlipidemia and high blood
pressure. However, some measured data itself cannot be simply combined
because of significant differences in units or numbers itself. On the
other hand, since relative values of the measured values is easy to be
combined, the health condition and the risk of progression to lifestyle
diseases can be easily determined.

[0045]Herein, the phrase "combines two or more of the physical data, the
blood components data and the relative values" includes the case in which
two or more elements are selected from one of the above three categories
(the physical data, the blood components data and the relative values),
the case in which one or more elements are respectively selected from two
of the above three categories, and the case in which one or more elements
are selected from each of the above three categories.

[0046]In the above configuration, the acquiring means may further comprise
total health assessment formula and total health condition determination
criteria, and the processing means combines two or more of the relative
values and the health condition determination relative values to
calculate total health condition determination relative values using the
total health assessment formula, and then may check the total health
condition determination relative values with the total health condition
determination criteria to determine total health condition of subjects.

[0047]"In order to totally determine health condition, it is preferable to
further combine two or more individual data and determination of the risk
of progression to lifestyle diseases by understanding the health
condition based on combination of a plurality of individual data. In this
case, the combination of relative values is also useful.

[0048]As a data conversion formula, a pattern table showing the
relationship between the relative values and the measurement values can
be used.

[0049]In the above configuration, several kinds of pattern tables are
obtained. The processing means determines at least one of sex, age and
race of the subjects and then decides the pattern table to be used.

[0050]Some physical data and blood components data may significantly vary
depending on the subject's sex, age and race. Therefore, use of the
pattern table suitable for the subject can provide more precise
determination of health condition. Moreover, other factors (being
pregnant or not, an athlete or not, etc.) may be further determined, and
then another pattern table may be decided in view of the factors.

[0051]In the above configuration, the health condition determination
apparatus may further comprise an input means.

[0052]In the above configuration, the health condition determination
apparatus may further comprise a display that informs the results of the
determination.

[0053]In the above configuration, the acquiring means may further acquire
health improvement data, and the processing means may check the
determination results with the health improvement data and then may let
the display show the determination results and the health improvement
method corresponding thereto.

[0054]The display shows the determination results and the health
improvement method corresponding thereto, which urges the subjects to
improve their own health.

[0055]In the above configuration, the acquiring means may further acquire
time course information on the determination results, and the display may
further inform the monitoring of the results with time.

[0056]Displaying the time course information results in easily
understanding whether the subject's health condition is being improved or
not.

[0058]The detection instruments can shorten the time from the analysis to
the determination.

[0059]The acquiring means may comprise a memory for recording various
information, such as a hard disk and a Flash SSD (Flash Solid State
Drive), or a communication means for obtaining various information via
electric communication lines such as Internet and other wired or wireless
communication lines.

[0060]The first aspect of the present invention relating to a health
condition determination method for solving the above problems is
characterized by comprising:

[0063]The above method allows the subjects to easily determine whether
each data is in the High Risk range or not.

[0064]The above configuration may further comprise:

[0065]a health condition determination relative values calculating step
for calculating relative values used in health condition determination by
combining two or more of the relative values and using health assessment
formula; and

[0066]a health condition determination step for determining the risk of
progression to lifestyle diseases of the subjects by check the health
condition determination relative values with health condition
determination criteria.

[0067]According to this configuration, it becomes easy to combine the
several data by using the relative values, and thus the health condition
and the risk of progression to lifestyle diseases can be easily
determined.

[0068]The health condition determination relative values calculation and
the determination of the risk of progression to lifestyle diseases may be
performed at the same time. In this case, the health assessment formula
may be integrated with the health condition determination criteria.

[0069]The second aspect of the present invention relating to a health
condition determination method for solving the above problems is
characterized by comprising:

[0071]a relative values conversion step for converting the physical data
and the blood components data into relative values based on results of
the data determination;

[0072]a health condition determination relative values calculating step
for combining two or more of the relative values and then calculating
relative values used in health condition determination by using health
assessment formula; and

[0073]a health condition determination step for determining the risk of
progression to lifestyle diseases of the subjects by check the health
condition determination relative values with health condition
determination criteria.

[0074]This configuration is similar to the above configuration except that
each data is determined before the conversion into the relative value and
then the data is converted into relative values on the basis of the
determination. Even in this configuration, several data can be easily
combined and thus the health condition can be easily determined.

[0075]The configuration may be also used in which the conversion of the
data into the relative values is performed in conjunction with the data
determination.

[0076]The above configuration of the first or second aspect of the present
invention may further comprise,

[0077]a total health condition determination relative values calculating
step for calculating relative values used in determination of total
health condition of subjects, by combining two or more of the relative
values and/or the health condition determination relative values and
using total health assessment formula; and

[0078]a total health condition determination step for determining total
health condition of the subjects by check the total health condition
determination relative values with total health condition determination
criteria.

[0079]In order to totally determine the health condition, it is preferable
to further combine individual data or health condition determination
based on combination of several individual data. Also in this case, a
combination of relative values is useful.

[0080]In the above configuration, the total health condition relative
values calculating and the total health condition determination may be
performed at the same time. In this case, the total health assessment
formula may be integrated with the total health condition determination
criteria.

[0081]In the above configuration, the health condition determination
relative values and/or the relative values may be at least one selected
from the group consisting of the Body Mass Index relative values, the
metabolic syndrome determination relative values and the specific
proteins in blood determination relative values.

[0082]In order to determine the risk of progression to lifestyle diseases,
it is preferable to determine the Body Mass Index relative values, the
metabolic syndrome determination relative values and the specific
proteins in blood determination relative values. Preferably, two or more
kinds of these relative values are combined to determine. More
preferably, all three kinds of these relative values are combined to
determine. Thereby, metabolic syndrome and the risk of progression to
lifestyle diseases can be determined in more detail.

[0083]The determination of metabolic syndrome may use the definition of
National Cholesterol Education Program (NCEP), International Diabetes
Federation (IDF) and the Japan Society of Obesity (JASSO). Or, other
definitions also may be used.

[0084]In the specific proteins in blood determination, it is preferable to
use the level in blood of at least one of adiponectin, leptin, resistin
and TNF-α, but also other components in blood could be used.

[0085]As a data conversion formula, a pattern table showing the
relationship between the measurement values and relative values can be
used.

[0086]As a health assessment formula, a formula to sum up relative values
in equal ratio or in different ratios for each data may be used. In
addition, when one kind of relative values exceeds a criteria value, the
health assessment relative values may be determined as "High Risk",
regardless of other relative values.

[0087]As a total health assessment formula, a formula to sum up relative
values in equal ratio or in different ratios for each data may be used.
In addition, when one kind of relative values or the total health
condition relative values exceeds a criteria value, the total health
assessment relative values may be determined as "High Risk", regardless
of other relative values.

[0088]The above configuration may further comprise a pattern table
deciding step to determine at least one of sex, age, race of subjects and
thus to decide the pattern table to be used.

[0089]The display method for showing the determination results according
to the present invention is characterized by that the relative values of
the analysis data on adiponectin, leptin, resistin and TNF-α are
displayed together with graphs.

[0090]The expression of adiponectin, leptin, resistin and TNF-α in
the relative values allows the risk to be easily understood.

[0091]The display form according to the present invention may show only
the relative values, or the absolute values together with the
corresponding relative value.

[0092]In the above configuration, the graph is preferably arranged so that
indices that have a strong degree of the antagonistic relationship and/or
correlation are placed adjacently to each other.

[0093]The above configuration may comprise a system in which time course
information on the measurement values of the above-mentioned four
components is shown together with graphs.

[0094]Displaying the time course information facilitates to understand
whether the health condition of the subjects is getting better or not.
The time course information may be displayed all times or only when
commanded to display it.

[0095]In the above configuration, when any of the determination results of
the above four components exceeds to the criteria value, a warning
message may be displayed.

[0096]With the warning message, the risk of progression to lifestyle
disease of subjects can be more easily understood.

[0097]In the above configuration, a health improvement method of the
subjects may be displayed together with the above determination results.

[0098]In the above configuration, when X1 is an adiponectin level, X2 is a
leptin level, X3 is a resistin level, and X4 is a TNF-α level, and
when coefficients of obesity degree determined by Body Mass Index
relative values are defined as Y1 and Y2, X1Y1, X2Y2, X3Y2 and X4Y1 may
be displayed.

[0099]In the above configuration, the parameters may be shown using a
human-shaped model, which displays X1Y1 at the right edge of the waist,
X2Y2 at the right edge of the chest, X3Y2 at the left edge of the chest,
and X4Y1 at the left edge of the waist. For this display, each of the
levels and values is multiplied by coefficients so as to be displayed at
the appropriate position.

[0100]In the above configuration, the parameters may be shown using
another human-shaped model, which displays X1Y1 at the back edge of the
waist, X2Y2 at the back edge of the abdomen, X3Y2 at the front edge of
the abdomen, and X4Y1 at the front edge of the waist.

[0101]The use of such display forms facilitates to understand health
condition visually.

[0102]In the present invention, in order to determine health condition of
the subjects, the physical data and blood data are converted into the
relative values. The combination of the relative values of the several
data provides the exact determination of health condition.

[0103]Also, displaying the determination results as well as a health
improvement method according to subjects' health condition allows the
improvement and prevention of lifestyle diseases, and thus facilitates
health control of the subjects.

[0104]In addition, since the health condition of the subjects is visually
and clearly displayed, effects of the improvement and prevention of
lifestyle diseases can be enhanced.

BRIEF DESCRIPTION OF THE DRAWINGS

[0105]FIG. 1 is a block diagram showing the configuration of the
healthcare management apparatus according to the present invention.

[0106]FIG. 2 is a block diagram showing the configuration of the
processing means used in the healthcare management apparatus according to
the present invention.

[0107]FIG. 3 is a diagram showing the display method for showing the
results of the total health condition determination according to
Embodiment 1.

[0108]FIG. 4 is a diagram showing a flow chart of the health condition
determining method according to Embodiment 1.

[0109]FIG. 5 is a diagram showing a flow chart of the health condition
determining method according to Embodiment 2.

[0110]FIG. 6 is a diagram showing a flow chart of the determining method
for metabolic syndrome according to Embodiment 2.

[0111]FIG. 7 is a diagram showing a flow chart of the determining method
for BMI according to Embodiment 2.

[0112]FIG. 8 is a diagram showing a flow chart of the health condition
determining method according to Embodiment 2.

[0113]FIG. 9 is a diagram showing a display form of the determination
results according to Embodiment 4.

[0114]FIG. 10 is a diagram showing another display form of the
determination results according to Embodiment 4.

DETAILED DESCRIPTION OF THE INVENTION

Embodiment 1

[0115]The apparatus for determining the health condition according to
Embodiment 1 is shown in FIG. 1.

[0116]The healthcare management apparatus according to this Embodiment
comprises a detection instrument 1 used in blood components analysis, an
analyzer 2 for analyzing a signal in the detection instrument and
converting into relative values, an input means 3 such as a keyboard or a
mouse, and a display 4 such as a liquid crystal display.

[0117]An external connection terminal 5 is provided on the detection
instrument 1, and inserted into a connection slot 6 of the analyzer 2.
The signal detected in the detection instrument 1 is delivered to the
analyzer 2.

[0118]As detection instrument 1, analytic microchip sensor with
microchannels proposed in Patent document 5 may be used. For example, in
the healthcare management apparatus for determining the risk of
progression to lifestyle diseases by using a specific proteins levels in
blood, it is preferable to select at least one of adiponectin, leptin,
resistin and TNF-α, preferably all of them, as a detection target.
Moreover, the levels of other blood components such as neutral fat, HDLc
and blood glucose may be detected. Regarding the analytic microchip
sensor used in these measurements, one microchip sensor may be used for
each component, or may detect multiple components.

[0119]The analytical microchip sensor can be used for detecting other
biological components in urine or salivary.

[0120]The detection instrument 1 is not essential to the system according
to the present invention. For example, the present invention may adopt
the configuration in which measured blood components data is input using
an input means, or the data is obtained via wired or wireless
communication lines.

[0121]As shown in FIG. 2, the analyzer 2 comprises a processing means such
as a central processing unit (CPU), a acquiring means having a memory
such as hard disk drive or Flash SSD (Flash Solid State Drive), an input
portion receiving an input of a input means and the like, an output
portion outputting to a display and the like, and an detection instrument
reading portion.

[0122]The memory stores various data such as physical data, blood
components data and identification characters, conversion formula (such
as pattern tables) used to calculate relative values, determination
criteria, and a method for the health improvement that corresponds to the
determination results. These may be stored in the same or different
memories.

[0123]The above acquiring means may comprise a communication means to
acquire various data via communication lines, instead of or together with
the memory. As communication lines, wired or wireless communication may
be used.

[0124]Identification characters of subjects are input from the input means
3, for example. The identification characters include, for example, each
person's name, identification number or identification mark, age, sex,
race and the like. Any one or more of these may be input in combination.
Usually, it is convenient to contain a subject's name in the
identification characters. Moreover, it is preferable to contain physical
data that is not changed quickly in the daily life (for example, height
of an adult person). Also, the identification characters may be acquired
via a communication means.

[0125]The physical data and blood component data may be input from the
input means. Or, as the physical data and blood component data, the data
into which the analyzer 2 converts signal from detection instrument 1
connected to the analyzer 2 may be used. These data may be stored in a
memory of the analyzer 2, or may be acquired via a communication means.

[0126]The display 4 displays the determination results and a health
improvement method based on the results.

(Health Condition Determination Method)

[0127]The health condition determination method according to this
Embodiment is specifically explained using an example to determine the
specific proteins in blood with reference to drawings. FIG. 4 is a
diagram showing a flowchart of the health condition determination method
(specific proteins in blood determination method) according to this
Embodiment.

[0128]In this embodiment, the levels of adiponectin, leptin, resistin and
TNF-α in blood are used as analysis data of blood components. And
with the combination of these data, the risk of developing lifestyle
diseases subjects is determined.

(Pattern Table Deciding Step)

[0129]The Normal or High Risk ranges of the above four components would be
different depending on sex, age, race and the like. Therefore, first, a
suitable kind of pattern tables (data conversion formula) for a subject
is decided.

[0130]The subject's identification characters stored in the memory are
determined by a processing means of the analyzer 2, and then a pattern
table according to a user's race (Mongoloid/Caucasian) and sex
(male/female) is decided.

(Detection Step)

[0131]Levels of the above four components in blood of the subject are
detected using the detection instrument 1. In the detection, a
conventional method may be used. For example, an analytic microchip
sensor may be used as the detection instrument 1 to detect the levels of
blood components using electrochemical method. And the electrochemical
detection, an optical or electrical detection means may be also used.

[0132]Optical signals or an electrical signals sent from the detection
instrument 1 are calculated at the analyzer 2 to work out each level of
the above four components.

(Relative Values Calculating Step)

[0133]The processing means of the analyzer 2 converts the levels of the
above four components into the relative values using the pattern table
(data conversion formula) decided in the above pattern table deciding
step.

[0134]Table 1 shown below can be used as a pattern table classified by
race and sex.

[0136]The processing means of the analyzer 2 sums up relative values the
above four components and converts the sum into health assessment
relative values using health assessment formula stored in the memory. As
health condition formula, Table 2 shown below can be used.

[0137]In the processing means of the analyzer 2, the health condition
determination relative values is checked up against the health condition
determination criteria shown below to determine the risk of progression
to lifestyle diseases of subjects.

[0139]The data determination step and the relative values calculating step
may be performed at the same time. Also, the health condition
determination step and the health condition determination relative values
calculating step may be performed at the same time.

(Display Method of the Determination Results)

[0140]Next, a method for displaying the results of the above determination
is explained.

[0141]FIG. 3 shows an example of the display method according to the
present invention. In this embodiment, it is exemplified that a display
shows a radar chart showing respective levels of adiponectin, leptin,
resistin and TNF-α along with its classification, a diagnostic
determination table, a diagnostic results and a health improvement
method.

[0142]The processing means compares the determination results with health
improvement method data (therapeutic methods) stored in the memory, which
correspond to the determination results, and thus shows an appreciate the
health improvement method.

[0144]The determination table shows the pattern table for "Mongoloid/Male"
and the stage into which each determination of the above four components
is classified.

[0145]On the radar chart color-coded on the basis of correspondence
between level and stage (relative values), the level of the above
adiponectin, leptin, resistin and TNF-α is plotted and then each
point is connected by solid lines.

In each axis of the radar chart, the degree of risk is increasing from the
center to the outward. Therefore, lower adiponectin level is positioned
more outside. In the case of the other three components, higher level is
positioned more outside. In the classification displayed together with
the components levels, "Normal" (0 points: Stage 4) is shown inside, and
"High Risk" (10 points: Stage 1) is shown outside.

[0146]In addition, it is preferable to color code the results. For
example, "Normal" (0 points) is green, "Attention" (5 points) is yellow,
"Warning" (8 points) is orange, and "High Risk" (10 points) is red.
Thereby, it is clarified what zone (health, attention, warning or high
risk) the quadrangle formed by connecting the respective component levels
is mainly contained in. As a result, the health condition can be visually
understood.

[0147]In this radar chart, it is preferable that indices having a strong
degree of the antagonistic relationship and/or the correlation are
arranged adjacently so that the health condition is easily understood.

[0148]For example, the relationship among these four components is
explained below.

[0149]It is known that metabolic syndrome results from the reason that the
adiponectin is decreased due to the production of TNF-α from fat
cells. Therefore, there is an antagonistic relationship between
TNF-α and adiponectin. That is, the more TNF-α, the less
adiponectin (cf. Non-patent document 1). Therefore, when adiponectin and
TNF-α are placed at the axes adjacent to each other, their
relationship is easy to be understood.

[0150]The relationship between metabolic syndrome and the ratio of
adiponectin and leptin is reported more often than adiponectin and leptin
itself (cf. Non-patent document 4). Therefore, adiponectin and leptin are
placed at the axes adjacent to each other. Thereby, the absolute value of
the slope of the solid lines connecting the value of adiponectin and
leptin corresponds to the ratio of adiponectin and leptin, which is
useful for the determination of metabolic syndrome.

[0151]In view of the above, each component is positioned as follows so
that adiponectin and TNF-α, and adiponectin and leptin are arranged
adjacently to each other, respectively.

[0152]Thereby, the results of the specific proteins in blood determination
(diagnosis) and the health improvement method respond to the
determination results (therapeutic method) are displayed.

[0153]In addition, when one or more past data are displayed together with
the latest data, time course information can be obtained and thus the
effects of therapy and prevention can be understood at a glance. In this
case, it is preferable that the latest data is visually discriminated
from the past data. For example, the quadrangle in the radar chart is
formed by solid lines for the latest data, and by dotted lines for the
past data.

[0154]In such a display method, when the quadrangle become smaller
compared with the past data, improved health is visually indicated. In
contrast, when the quadrangle become larger, it means undesirable.

[0155]It is known that the above four components is closely related to
lifestyle diseases associated with metabolic syndrome. For example, it is
reported that high leptin level and low adiponectin level result in the
higher risk of a stroke (cf. Non-patent document 1). Therefore, when at
least one of the component levels exceed the criteria value (for example,
when the relative value of the above determination is 10 points: Stage
1), the prompt meaning the high risk of progression to lifestyle diseases
(a warning message) is indicated to a user. This helps the user to figure
out their symptoms at a glance.

[0156]In addition, for example, when the plots in the screen (input means)
would be pointed by cursor, the plot of each component levels would be
shown and a time course graph that shows a time course of the respective
component levels may be displayed. This graph shows time on the
horizontal and the component levels on the vertical axis. That is, it
shows the respective component levels for each measurement date.
Similarly to the radar chart, it is preferable that "normal",
"attention", "warning" and "high risk" are color coded in the time course
graph.

[0157]This kind of graph provides a trend of change, and thus facilitates
to judge whether exercise, diet or a medicine is effective or not.

Embodiment 2

[0158]FIG. 5 is a diagram showing a flow chart of the health condition
determining method according to Embodiment 2.

[0159]In this embodiment, an example is explained in which the following
three determinations of health condition are performed, results of these
determination are combined, and then a total health condition
determination of subjects is performed. Since the configuration of the
health condition determination apparatus is similar to Embodiment 1, its
explanation is omitted.

[0160]In the metabolic syndrome determination, definitions disclosed by
National Cholesterol Education Program (NCEP), International Diabetes
Federation (IDF) and the Japan Society of Obesity (JASSO), etc. can be
used, or other definitions can be also used.

[0161]In this embodiment, the definition of the International Diabetes
Federation is used for the determination of metabolic syndrome.
Therefore, the physical data and blood components data used in the
metabolic syndrome determination are as follows.

[0174]According to the pattern table shown in Table 3, the individual
physical data and blood components data are converted into the relative
values. The waist circumference is divided into "match" (10 points) and
"not match" (0 points). The items other than the waist circumference are
divided into "match" (1 point) and "not match" (0 points).

(Health Condition Determination Relative Values Calculating Step)

[0175]The individual physical data and the blood components data are
summed up and the summed points are converted into the relative values
for metabolic syndrome determination using the metabolic syndrome
determination formula shown below (S5).

(Metabolic Syndrome Determination Formula)

TABLE-US-00005
[0176] The total points are 12 points or more: 10 points
The total points are 2 to 4 points, or 11 points: 5 points
The total points are 10 points, or 1 point or less: 0 points

[0179]BMI (Body Mass Index) is physical data represented by the following
formula:

BMI=Body weight (kg)/Body height (m) 2

(Relative Values Calculating/Data Determination Step)

[0180]The BMI data is determined to divide into the four groups:
High-degree obesity, Obesity, Normal and Slim. And each of the
determination results is converted into relative values. The data
determination criteria/data conversion formula of BMI is shown in Table
4.

[0182]The total health condition determination relative values are
calculated by combining the relative values of the above three different
determination results. In the total health assessment formula used for
calculating the total health condition determination relative values,
each determination result is obtained as shown below.

[0184]The resulting total health condition determination relative values
are compared with the total health condition determination criteria shown
below to determine the total health condition of the subjects.

(Total Health Condition Determination Criteria)

[0185]0 to less than 4.0: Normal4.0 to less than 6.8: Attention

6.8 to 10.0: High Risk

[0186]For example, if the metabolic syndrome determination is "High Risk",
BMI determination is "Obesity", and the specific proteins in blood
determination is "High Risk", then the total health condition
determination relative value is calculated as follows:

[0187]Therefore, the total health condition is determined as "High Risk".

[0188]Although, body weight is dependent on volume (cube of body height),
since BMI indicates body weight divided by square of body height, a tall
parson tends to be determined as "Obesity". For this reason, another BMI
determination criteria for a tall person (for example, 185 cm or more)
may be used.

Embodiment 3

[0189]In this embodiment, when any of the three health condition
determinations are determined as "High Risk" in Embodiment 2, the total
determination is defined as "High Risk". The Step to calculate the health
condition determination relative values and the steps before it are
similar to Embodiment 2, and thus the explanation is omitted.

[0196]The total health assessment formula is similar to Embodiment 2. The
total health condition determination criteria is as follows.

(Total Health Condition Determination Criteria)

[0197]0 to less than 4.0: Normal4.0 to less than 6.8: Attention6.8 or
more: High Risk

[0198]In the total health assessment according to this embodiment, when at
least one of metabolic syndrome determination estimated as "High Risk",
BMI determination estimated as "high-degree obesity" and specific
proteins in blood determination estimated as "High Risk" are applied, the
total health condition determination relative value is defined as 20
points or more, regardless of the other determinations. This allows early
improvement of health.

[0199]Further, the determination criteria may be changed as follows.

(Metabolic Syndrome Determination Criteria)

TABLE-US-00010
[0200] The total points are 12 points or more: 250 points
The total points are 2 to 4 points or 11 points: 5 points
The total points are 10 points, or 1 point or less: 0 points

[0203]In this case, when the above total health assessment formula is
used, the hundreds digit of the total point indicates whether the
metabolic syndrome determination is "High Risk" or not, the thousands
digit indicates whether the BMI determination is "High-degree obesity" or
not, and the ten thousands digit indicates whether the specific proteins
in blood determination is "High Risk" or not. This provides an easy
determination of the total health condition.

Embodiment 4

[0204]In this embodiment, the method for displaying the determination
results is explained. The determination method is performed according to
Embodiments 2 and 3.

[0205]FIG. 9 shows the display method according to this embodiment. In
FIG. 9, X1 is the level of adiponectin, X2 is the level of leptin, X3 is
the level of resistin, and X4 is the level of TNF-α. Y1 and Y2 is a
coefficient of obesity degree determined by Body Mass Index relative
value.

[0206]The dash (') attached to the BMI determination means the decision of
obesity by BMI determination. When the dash (') is not attached, it means
normal in view of BMI determination.

[0207]In FIG. 9, the parameters is shown using a human-shaped model, which
displays X1Y1 at the right edge of the waist, X2Y2 at the right edge of
the chest, X3Y2 at the left edge of the chest, and X4Y1 at the left edge
of the waist.

[0208]Such a display forms facilitates to visually understand whether of
the risk of progression to lifestyle diseases is low (FIG. 9 (a)) or high
(FIG. 9 (b)).

[0209]In addition, as shown in FIG. 10, the parameters may be shown using
another human-shaped model, which displays X1Y1 at the back edge of the
waist, X2Y2 at the back edge of the abdomen, X3Y2 at the front edge of
the abdomen, and X4Y1 at the front edge of the waist.

[0210]As described above, according to the present invention, the health
condition and the risk of progression to lifestyle diseases of subjects
can conveniently determined. This can promote early health improvement of
subjects and provides a noticeable effect in the prevention of lifestyle
diseases. Therefore, the significance of the present invention is great.